Out-of-pocket payments and catastrophic expenditures due to traffic injuries in Ouagadougou, Burkina Faso
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To estimate the out-of-pocket expenditures linked to Road Traffic Injuries in Ouagadougou, Burkina Faso, as well as the prevalence of catastrophic expenditures among those out-of-pocket payments, and to identify the socio-economic determinants of catastrophic expenditures due to Road Traffic Injuries. METHODS: We surveyed every admission at the only trauma unit of Ouagadougou between January and July 2015 at the time of their admission, 7 days and 30 days later. We estimate a total amount of out-of-pocket expenditures paid by each patient. We considered an expense as catastrophic when it represented 10% at least of the annual global consumption of the patient's household. We used linear models to determine if socio-economic characteristics were associated to a greater or smaller ratio between out-of-pocket payment and global annual consumption. FINDINGS: We surveyed 1323 Road injury victims three times (admission, Days 7 and 30). They paid in average 46,547 FCFA (83.64 US dollars) for their care, which represent a catastrophic expenditure for 19% of them. Less than 5% of the sample was covered by a health insurance scheme. Household economic status is found to be the first determinant of catastrophic health expenditure occurrence, exhibiting a significant and negative on the ratio between road injury expenditures and global consumption. CONCLUSION: Our findings highlight the importance of developing health insurance schemes to protect poor households from the economic burden of road traffic injuries and improve equity in front of health shocks.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it